{"id":"W7052365046","doi":"","title":"Reducing Potentially Inappropriate Medications in Older Adults: A Way Forward","year":2019,"lang":"fr","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Particle Accelerators and Free-Electron Lasers","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"MEDLINE; Disease; Older people; Population ageing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002643992,0.0004018073,0.0004394516,0.006704918,0.0001166869,0.00007730086,0.0005577517,0.0003397272,0.0003044833],"category_scores_gemma":[0.00003776105,0.0004977672,0.000191084,0.008876652,0.0001006246,0.0009860004,0.0001794114,0.0006603153,0.0003321214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009504907,"about_ca_system_score_gemma":0.000508615,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08624353,"about_ca_topic_score_gemma":0.01721738,"domain_scores_codex":[0.9974827,0.0001538359,0.0003979671,0.0006575161,0.0003104457,0.0009975323],"domain_scores_gemma":[0.9988439,0.00007099552,0.0001315137,0.0006182444,0.0001206262,0.0002147272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001354164,0.003689634,0.02789052,0.003309255,0.002146918,0.001961364,0.08151154,0.03301745,0.00294744,0.0347966,0.003417245,0.8039579],"study_design_scores_gemma":[0.004935009,0.0002299206,0.003615651,0.0008579459,0.0002209719,0.00002310051,0.00207032,0.0474594,0.002875232,0.000003963633,0.9368531,0.0008553626],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8376822,0.00008960244,0.003639593,0.0009487778,0.001200658,0.001379417,0.00005237701,0.000282198,0.1547251],"genre_scores_gemma":[0.9336889,0.06359901,0.002091607,0.00005463976,0.0001639207,0.000009181877,0.00003534959,0.00007961925,0.0002777953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9334359,"threshold_uncertainty_score":0.9997474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007503850795645898,"score_gpt":0.1992840098887083,"score_spread":0.1917801590930624,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}